Present techniques for functional MRI rely on detecting changes in hemodynamics that result as a consequence of brain activation. It would be useful if MRI techniques could be developed that enable imaging of a parameter directly related to neuronal activity. Influx of calcium into neurons is necessary for release of neurotransmitters. Divalent manganese ions (Mn") can enter cells through voltage-gated calcium channels and Mn2+ is paramagnetic. Mn2+ accumulation in br.ain due to activation should alter relaxation times offering an approach to sensitize MRI to calcium influx in the brain. To test this idea, T,-weighted MRI was obtained from the rat brain in the presence of a continuous intravenous infusion of 3.6 pnol/min MnCI,. In the anesthetized rat brain, signal enhancement was detected in regions corresponding to ventricles. Activation of the brain with glutamate led to increase in MRI signal intensity in the brain to 238 2 23% of the original. This increase in signal was dependent on the presence of MnCI, and was not due to changes in blood flow. It was necessary to break the blood brain barrier with mannitol to make Mn" accessible to the active sites for efficient detection. Enhancement of MRI signal in the brain was also detected with decreasing anesthesia and with somatosensory stimulation. Due to the slow clearance of Mn2+ from the stimulated region of the brain, MRI enhancement could also be detected after stimulation that occurred on awake, behaving rats outside the magnet. These data indicate that MnCI, shows potential as a MRI contrast agent that is directly sensitive to brain activation.

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This paper investigated the nature of social support for Asian‐ and Anglo‐American women post breast cancer treatment. Forty‐six Anglo‐ and Asian‐American (13 Anglo‐American, 18 Chinese‐American and 15 Japanese‐American women) women were assessed 6 months to 3 years post‐treatment. Assessments consisted of a semi‐structured interview plus standardized psychological tests. Three major hypotheses were developed and tested in the study. Results showed: (1) Anglo‐American women indicated a greater need for social support than either of the two Asian‐American groups in 66% of the categories; (2) no differences were found between the three ethnic groups in receipt of emotional or tangible social support; and (3) the network size and composition differed significantly in 83% of the categories between the Anglo group and at least one of the Asian groups. These differences were in size, mode, and perceived adequacy of social support. Implications for culturally‐based clinical practice which emerge from these findings are discussed. Copyright © 1999 John Wiley & Sons, Ltd.

Abstract-Clustering is an important research topic in wireless networks, because cluster structures can facilitate resource reuse and increase system capacity. In this paper, we present a new clustering algorithm that considers both node position and node mobility in vehicular ad hoc environments. The proposed algorithm intends to create stable clusters by reducing reclustering overhead, prolonging cluster lifetime, and shortening the average distance between cluster heads and their cluster members. Most important, this algorithm supports single and multiple cluster heads. Simulation results show the superiority of our clustering algorithm over the other three well-known algorithms.

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This paper proposes a torque ripple reduction for brushless DC (BLDC) permanent magnetic (PM) motor drive based on the DC-link voltage pulse amplitude modulation (PAM). The proposed method improves torque ripple drawback for BLDC drives at low speed. BLDC drives have the better inverter efficiency and requires low position sensing resolution. However, both freewheeling current during diode conduction and discontinuous motor phase current cause high torque ripples. In this paper, a frontend DC converter is added to improve BLDC torque ripples. Although the integration of DC converter and BLDC drive has been reported, the DC voltage regulation for the BLDC torque ripple compensation is this paper novelty. On the basis, the DC bus is modulated during diode conduction to manipulate the DC current dynamically every BLDC commutation period. In addition considering the discontinuous sixstep commutation, the DC current is also regulated with the 6th-order spatial harmonic to minimize the commutation reflected torque ripple. The proposed torque ripple compensation of BLDC drive is verified by simulation for different PM motor types. According to experimental results, around 40% torque ripple reduction on a PM motor is demonstrated using the proposed BLDC drive with DC voltage modulation.

For pulse width modulation (PWM) inverter drives, an LC filter can cascade to a permanent magnet (PM) machine at inverter output to reduce PWM-reflected current harmonics. Because the LC filter causes resonance, the filter output current and voltage are required for the sensorless field-oriented control (FOC) drive. However, existing sensors and inverters are typically integrated inside commercial closed-form drives; it is not possible for these drives to obtain additional filter output signals. To resolve this integration issue, this paper proposes a sensorless LC filter state estimation using only the drive inside current sensors. The design principle of the LC filter is first introduced to remove PWM current harmonics. A dual-observer is then proposed to estimate the filter output current and voltage for the sensorless FOC drive. Compared to conventional model-based estimation, the proposed dual-observer demonstrates robust estimation performance under parameter error. The capacitor parameter error shows a negligible influence on the proposed observer estimation. The filter inductance error only affects the capacitor current estimation at high speed. The performance of the sensorless FOC drive using the proposed dual-observer is comparable to the same drive using external sensors for filter voltage and current measurement. All experiments are verified by a PM machine with only 130 μH phase inductance.

This paper proposes a novel torque measurement and control technique for cycling-assisted electric bikes (E-bikes) considering various external load conditions. For assisted E-bikes, the electromagnetic torque from the permanent magnet (PM) motor can be controlled to reduce the pedaling torque generated by the human rider. However, the overall cycling torque is affected by external loads, including the cyclist’s weight, wind resistance, rolling resistance, and the road slope. With knowledge of these external loads, the motor torque can be adaptively controlled for these riding conditions. In this paper, key E-bike riding parameters are analyzed to find a suitable assisted motor torque. Four different motor torque control methods are proposed to improve the E-bike’s dynamic response with minimal variation in acceleration. It is concluded that the wheel acceleration is important to determine the E-bike’s synergetic torque performance. A comprehensive E-bike simulation environment is developed with MATLAB/Simulink to evaluate these adaptive torque control methods. In this paper, an integrated E-bike sensor hardware system is built to verify the proposed adaptive torque control.